EPAM Systems vs Tensorway: full comparison for 2026
Quick verdict
EPAM Systems (4.6/5) edges ahead of Tensorway (4.4/5) overall. EPAM Systems is the better choice for large enterprises, regulated industries, multi-team AI programs. Tensorway is the stronger option for product teams adding senior AI specialists without vendor lock-in. The right choice depends on your project size, budget, and required tech stack.
EPAM Systems vs Tensorway: head-to-head summary
| Criterion | EPAM Systems | Tensorway |
|---|---|---|
| Founded | 1993 | 2019 |
| HQ | Newtown, Pennsylvania, USA | Alicante, Spain |
| Team size | 61,000+ | 50–249 |
| Rating | 4.6 / 5 | 4.4 / 5 |
| Primary differentiator | Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes | Senior AI engineers run the technical screening, and every model and line of code stays in the client's repositories |
| Pricing model | Time and materials for augmented engineers; dedicated team and managed program contracts; rates on request | Monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request |
| Min. engagement | Not published | Not disclosed |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, PyTorch, TensorFlow |
| Industries served | Financial services, Healthcare & life sciences, Retail & e-commerce, Software & SaaS, Travel, Manufacturing | Financial services, Software & SaaS, Healthcare & life sciences, Logistics, Manufacturing |
EPAM Systems vs Tensorway: overview
EPAM Systems
EPAM Systems was founded in 1993 and is headquartered in Newtown, Pennsylvania, with roughly 61,000 employees across delivery centers in Europe, the Americas and Asia. It is a public company listed on the New York Stock Exchange. On its Q2 2026 earnings call, management said EPAM had more than 5,700 Anthropic-certified engineers and was among the five largest certified partners worldwide, with AI-native work making up about 11% of revenue. EPAM employs its engineers directly and sells them as augmented capacity, dedicated teams or managed programs, though most large accounts end up in the managed model.
Tensorway
Tensorway, founded in 2019 and based in Alicante, Spain, supplies AI engineers who join a client's own team and work inside its Slack, Jira and version control under its coding standards. The firm has more than 20 years of software engineering practice behind its delivery methods. Its central promise concerns ownership: code, documentation and trained models stay in the client's repositories, and knowledge transfer to in-house staff is part of every engagement (per company website; independently unverifiable). Available roles include LLM engineers, RAG specialists, MLOps architects, computer-vision and NLP engineers, with teams usually starting as a squad of two to five. In one published case, a U.S. trading platform serving more than 100,000 investors reports 40% faster market-data processing and 35% lower operating costs (per company website; independently unverifiable).
Services and capabilities: EPAM Systems vs Tensorway
| Capability | EPAM Systems | Tensorway |
|---|---|---|
| LLM / GenAI engineers | ✓ | ✓ |
| MLOps & deployment | ✓ | ✓ |
| Computer vision | ✗ | ✓ |
| Data engineering | ✓ | ✗ |
| AI agent development | ✓ | ✗ |
| Fractional / part-time experts | ✗ | ✓ |
| Risk-free trial period | ✗ | ✓ |
| Nearshore time-zone overlap | ✗ | ✗ |
Tech stack comparison: EPAM Systems vs Tensorway
| Framework / platform | EPAM Systems | Tensorway |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| LangChain | ✓ | ✓ |
| Hugging Face | N/A | ✓ |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Databricks | ✓ | N/A |
| MLflow | N/A | ✓ |
| Kubernetes | ✓ | ✓ |
Pricing comparison: EPAM Systems vs Tensorway
| Criterion | EPAM Systems | Tensorway |
|---|---|---|
| Minimum engagement | Not published | Not disclosed |
| Engagement models | Full-time dedicated engineers, Dedicated team, Managed delivery | Full-time dedicated engineers, Part-time fractional experts, Trial period |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: EPAM Systems vs Tensorway
| Dimension | EPAM Systems | Tensorway |
|---|---|---|
| Best company size | Mid-market to enterprise | Startup to mid-market |
| Best industries | Financial services, Healthcare & life sciences, Retail & e-commerce | Financial services, Software & SaaS, Healthcare & life sciences |
| Best use cases | Adding a 15-person GenAI squad to a bank's existing platform team, Rolling out agentic workflows across several business units under one master agreement | Adding RAG and evaluation expertise to a SaaS team shipping its first LLM feature, Bringing GPU inference costs under control for a production model |
| Typical project type | Full-time dedicated engineers | Full-time dedicated engineers |
EPAM Systems vs Tensorway: pros and cons
| EPAM Systems | |
|---|---|
| + | A Q2 2026 earnings call put its Anthropic-certified engineer count above 5,700, the largest verified GenAI bench on this list |
| + | Public-company reporting, audited financials and mature security reviews make vendor onboarding easier at banks and insurers |
| + | Can staff ten or more AI engineers in parallel across several time zones without running out of senior people |
| + | Deep data-platform practice means LLM work and the data engineering under it can come from one supplier |
| - | Rates are among the highest on this list and are only shared after scoping |
| - | Small requests for one or two engineers rarely get the same attention as large programs |
| - | Engagements tend to drift toward managed delivery, which moves decisions away from your own team |
| Tensorway | |
|---|---|
| + | Candidates pass a code review, a practical task in their specialty and a communication check run by senior AI engineers |
| + | Clients keep all code, documentation and trained models in their own repositories |
| + | First engineer typically starts in one to two weeks and a full squad in three to four (per company website; independently unverifiable) |
| + | Engineers bring GPU and inference cost control, fine-tuning and vector-database experience |
| + | Commitment is monthly and can be adjusted between sprints, with no-cost replacement for a poor fit |
| - | No public rate card, so budgeting starts with a sales call |
| - | Its bench is far smaller than EPAM's or Turing's, which limits how many engineers can start at once |
| - | Only AI and ML roles are offered, so general full-stack or QA staffing has to come from elsewhere |
Who should choose EPAM Systems?
A typical fit: adding a 15-person GenAI squad to a bank's existing platform team.
Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Healthcare & life sciences, Retail & e-commerce, Software & SaaS, Travel, Manufacturing.
Who should choose Tensorway?
A typical fit: adding RAG and evaluation expertise to a SaaS team shipping its first LLM feature.
Senior AI engineers run the technical screening, and every model and line of code stays in the client's repositories. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Software & SaaS, Healthcare & life sciences, Logistics, Manufacturing.
Decision matrix: EPAM Systems vs Tensorway
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | EPAM Systems |
| You want the supplier to own delivery as well as staffing | EPAM Systems |
| You need one expert part-time | Tensorway |
| You want to test an engineer before signing for months | Tensorway |
| Your budget is at the lower end | Compare: EPAM Systems (Not published) vs Tensorway (Not disclosed) |
| You need overlap with U.S. working hours | Neither is nearshore; agree overlap hours up front |
| You need specialist depth in a specific vertical | EPAM Systems |
Use case fit: EPAM Systems vs Tensorway
| Use case | EPAM Systems fit | Tensorway fit | Winner |
|---|---|---|---|
| Adding a 15-person GenAI squad to a bank's existing platform team | Strong | Strong | Both equally |
| Rolling out agentic workflows across several business units under one master agreement | Strong | Limited | EPAM Systems |
| Adding RAG and evaluation expertise to a SaaS team shipping its first LLM feature | Strong | Strong | Both equally |
| Bringing GPU inference costs under control for a production model | Limited | Strong | Tensorway |
Verdict: EPAM Systems vs Tensorway
EPAM Systems (4.6/5) is the stronger overall choice for most AI Staff Augmentation projects. Thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes.
Tensorway (4.4/5) is worth a look if you need bringing GPU inference costs under control for a production model. If your situation matches that, Tensorway is a competitive option.
Related comparisons
EPAM Systems vs Tensorway FAQ
Is EPAM Systems better than Tensorway?
EPAM Systems (4.6/5) scores higher overall, but "better" depends on your use case. EPAM Systems's strongest advantage: a Q2 2026 earnings call put its Anthropic-certified engineer count above 5,700, the largest verified GenAI bench on this list. Tensorway's strongest advantage: candidates pass a code review, a practical task in their specialty and a communication check run by senior AI engineers.
How do EPAM Systems and Tensorway differ in pricing?
EPAM Systems uses time and materials for augmented engineers; dedicated team and managed program contracts; rates on request pricing. Tensorway uses monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: EPAM Systems or Tensorway?
EPAM Systems is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between EPAM Systems and Tensorway?
EPAM Systems's primary differentiator is: thousands of certified GenAI engineers inside a publicly listed firm with enterprise security and procurement processes. Tensorway's primary differentiator is: senior AI engineers run the technical screening, and every model and line of code stays in the client's repositories. They also differ in team size (61,000+ vs 50–249), minimum engagement (Not published vs Not disclosed), and primary industries served (Financial services, Healthcare & life sciences vs Financial services, Software & SaaS).
Verify all details directly with each company before making a decision.